View PDF ↗
PDF Viewer
Open Full PDF

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (23)

[1]
MoNaCo: More Natural and Complex Questions for Reasoning Across Dozens of Documents
2025Tomer Wolfson, H. Trivedi et al.
[2]
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
2025Gheorghe Comanici, Eric Bieber et al.
[3]
OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
2025Mengkang Hu, Yuhang Zhou et al.
[4]
WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratch
2025Zimu Lu, Yunqiao Yang et al.
[5]
BrowseComp: A Simple Yet Challenging Benchmark for Browsing Agents
2025Jason Wei, Zhiqing Sun et al.
[6]
PaperBench: Evaluating AI's Ability to Replicate AI Research
2025Giulio Starace, Oliver Jaffe et al.
[7]
Evaluating Step-by-step Reasoning Traces: A Survey
2025Jinu Lee, J. Hockenmaier
[8]
KernelBench: Can LLMs Write Efficient GPU Kernels?
2025Anne Ouyang, Simon Guo et al.
[9]
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning
2025DeepSeek-AI, Daya Guo et al.
[10]
MMQA: Evaluating LLMs with Multi-Table Multi-Hop Complex Questions
2025Jian Wu, Linyi Yang et al.
[11]
Measuring short-form factuality in large language models
2024Jason Wei, Nguyen Karina et al.
[12]
MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
2024Jun Shern Chan, Neil Chowdhury et al.
[13]
AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?
2024Ori Yoran, S. Amouyal et al.
[14]
Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems
2024Tamer Abuelsaad, Deepak Akkil et al.
[15]
Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models - A Survey
2024Philipp Mondorf, Barbara Plank
[16]
Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning
2024Debjit Paul, Robert West et al.
[17]
Executable Code Actions Elicit Better LLM Agents
2024Xingyao Wang, Yangyi Chen et al.
[18]
GAIA: a benchmark for General AI Assistants
2023G. Mialon, Clémentine Fourrier et al.
[19]
SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
2023Carlos E. Jimenez, John Yang et al.
[20]
REFINER: Reasoning Feedback on Intermediate Representations
2023Debjit Paul, Mete Ismayilzada et al.

Showing 20 of 23 references

Founder's Pitch

"Develop DEEPSYNTH, a benchmark to evaluate AI agents' ability to synthesize information across multiple domains and data sources."

AI EvaluationScore: 5View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

2/4 signals

5

Series A Potential

1/4 signals

2.5

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 2/24/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.